Incrementally Building Topology Graphs via Distance Maps
Yijun Yuan, S\"oren Schwertfeger

TL;DR
This paper introduces a novel incremental framework for building topological maps using distance maps, enabling robots to grow their environment representation as new sensor data is received.
Contribution
The paper presents a new method for incrementally constructing topological graphs with distance maps, advancing robotic mapping capabilities.
Findings
Successfully demonstrated on various maps
Enables real-time growth of topological maps
Applicable to robot exploration scenarios
Abstract
Mapping is an essential task for mobile robots and topological representation often works as a basis for the various applications. In this paper, a novel framework that can build topological maps incrementally is proposed. The algorithm is using a distance map, and in our framework the topological map can grow as we append more sensor data to the map. To demonstrate our algorithm, we show the result of the distance map based method on several popular maps and run the incremental framework with raw sensor data to have a growing topological map, as an example of a robot exploring the environment.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsRobotic Path Planning Algorithms · Robotics and Sensor-Based Localization · Modular Robots and Swarm Intelligence
